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Abstrakty
Purpose: The article aimed to identify differences in the density of the trust network of team members in different work models (on-site, hybrid, and remote) and to identify opportunities for building knowledge and innovation in such work models based on the trust there. The method of experiment and a social networks analysis (SNA) was used to achieve the goal. Design/methodology/approach: The research is based on an experiment as part of a strategic business simulation game. The participants of the investigation are MBA students. The variable in the experiment is the work model. In these three different situations, relationships developed in teams are identified. Based on the identified relationships, visualizations of the trust network were built. Findings: The research confirmed that the hybrid and remote work models minimize the number of trust ties between team members. The network of trust based on the identified relationships is less dense. The decline in confidence leads to the conclusion that a company's innovation and ability to generate new knowledge are now under threat based only on group resources. Research limitations/implications: Research is based on an experiment. The group subjected to the investigation is MBA students. The limited duration of the experiment may limit the formation of networks of trust (based on long-term, deep relationships). See also a summary. Practical implications: The results indicate apparent differences in the density of trust relations between the organization's participants in the three analyzed work models. This points directly to the need to adjust tools supporting the development of innovation and knowledge creation for remote work models, different from those known from traditional (on-site) work models. Originality/value: The study shows that trust relationships, e are more challenging to achieve in remote working conditions than in traditional work models. It gives managers guidelines on what tools (such as SNA) they can use to identify relationships between people in new work models.
Rocznik
Tom
Strony
691--705
Opis fizyczny
Bibliogr. 38 poz.
Twórcy
autor
- Department of Management Systems Design, Wrocław University of Economics and Business, Poland
Bibliografia
- 1. Adler, P.S., Kwon, S. (2002). Social capital: prospects for a new concept. Academy of Management Review, 27(1), pp. 17-40, https://doi.org/10.2307/4134367.
- 2. Alsallakh, B. Micallef, L., Aigner, W., Hauser, H., Miksch, P., Rodgers, P. (2014). Visualizing sets and set-typed data: State-of-the-art and future challenges, http://dx.doi.org/10.2312/eurovisstar.20141170.
- 3. Anklam, P. (2007) Net work: a practical guide to creating and sustaining networks at work and in the world. Place: Routledge.
- 4. Baker, W.E., Faulkner R.R. (2017). Interorganizational networks. The Blackwell companion to organizations, pp. 520-540, https://doi.org/10.1002/9781405164061.ch22.
- 5. Borgatti, S.P., Everett, M.G., Johnson, J.C. (2018). Analyzing social networks. Place: Sage.
- 6. Borgatti, S.P., Foster, P.C. (2003). The network paradigm in organizational research: A review and typology. Journal of management, vol. 29, no. 6, pp. 991-1013, https://doi.org/10.1016/S0149-2063(03)00087-4.
- 7. Borgatti, S.P., Mehra, A., Brass, D.J., Labianca, G. (2009). Network analysis in the social sciences. Science, vol. 323, no. 5916, pp. 892-895, DOI: 10.1126/science.116582.
- 8. Borgatti, S.P., Halgin, D. (2013). On Network Theory. Organization science, vol. 22, no. 5, pp. 1168-1181, http://dx.doi.org/10.2139/ssrn.2260993.
- 9. Borgatti, S.P., Brass, D.J., Halgin, D.S. (2014). Social Network Research: Confusions, Criticisms, and Controversies, Contemporary Perspectives on Organizational Social Networks (Research in the Sociology of Organizations, Vol. 40). Bingley: Emerald Group Publishing Limited, pp. 1-29. https://doi.org/10.1108/S0733-558X(2014)0000040001.
- 10. Brass, D.J., Butterfield, K.D., Skaggs, B.C. (1998). Relationships and unethical behavior: A social network perspective. Academy of management review, vol. 23, no. 1, pp. 14-31, https://doi.org/10.5465/amr.1998.192955.
- 11. Burt, R.S. (2004). Structural holes and good ideas. American Journal Of Sociology, vol. 110, no. 2, pp. 349-399, https://doi.org/10.1086/421787.
- 12. Burt, R. (1992). Structural Holes. Contemporary Sociological Theory, p. 204.
- 13. Burt, R.S. (1992). Structural Holes: The Social Structure of Competition. Cambridge, Massachussetts, and London, England: Harvard University Press.
- 14. Cross, R., Parker, A., Borgatti, S.P. (2002). A bird’s-eye view: Using social network analysis to improve knowledge creation and sharing. IBM Institute for Business Value, pp. 1669-1600, https://www-07.ibm.com/services/hk/strategy/pdf/a_birds_eye_view.pdf, 18.02.2018.
- 15. Cross, R., Thomas, R.J., Light, D.A. (2009). How’who you know’affects what you decide. MIT Sloan Management Review, vol. 50, no. 2, p. 35, https://sloanreview.mit.edu/article/ how-who-you-know-affects-what-you-decide/, 20.10.2021.
- 16. Grant, R. (2018). Data visualization: charts, maps, and interactive graphics. Place: Chapman and Hall/CRC.
- 17. Green, D., The role of Organizational Network Analysis in People Analytics. Retrieved from: https://www.linkedin.com/pulse/role-organisational-network-analysis-people-analytics-david-green/, 26.11.2018.
- 18. Gulati, R., Dialdin, D.A., Wang, L. (2017). Organizational networks. The Blackwell companion to organizations, pp. 281-303, doi.org/10.1002/9781405164061.ch12.
- 19. Hansen, M.T. (1999). The search-transfer problem: The role of weak ties in sharing knowledge across organizational subunits. Administrative Science Quarterly, 44, pp. 82¬111, https://doi.org/10.2307/26670.
- 20. Kilduff, M., Krackhardt, D. (1994). Bringing the individual back in: A structural analysis of the internal market for reputation in organizations. Academy of Management Journal, vol. 37, no. 1, pp. 87-108, https://doi.org/10.2307/256771.
- 21. Kutik, B., Time to Care About ONA! Retrieved from: https://hrexecutive.com/time-to-care- about-ona, 5.12.2019.
- 22. Lewis, T.G. (2009). Network science: theory and practice. Place: Wiley.
- 23. MacGeorge, E.L., Guntzviller, L.M., Hanasono, L.K, Feng, B. (2016). Testing advice response theory in interactions with friends. Communication Research, vol. 43, no. 2, pp. 211-231, https://doi.org/10.1177/0093650213510938.
- 24. Moran, P. (2005). Structural vs. relational embeddedness: social capital and managerial performance. Strategic Management Journal, 26(12), pp. 1129-1151, https://doi.org/ 10.1002/smj.486.
- 25. Munzner, T. (2014). Visualization Analysis and Design. A K Peters/CRC Press.
- 26. Nahapiet, J. Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), pp. 242-266, https://doi.org/ 10.2307/259373.
- 27. Obstfeld, D. (2005). Social networks, the tertius iungens orientation, and involvement in innovation. Administrative science quarterly, vol. 50, no. 1, pp. 100-130, https://doi.org/10.2189/asqu.2005.50.1.100.
- 28. Okoe, M., Jianu, R., Kobourov, S. (2018). Node-link or adjacency matrices: Old question, new insights. IEEE Transactions On Visualization And Computer Graphics, vol. 25, no. 10, pp. 2940-2952, doi: 10.1109/TVCG.2018.2865940.
- 29. Polyakova, A., Loginov, M., Strelnikov, E., Usova, N. (2019). Managerial decision support algorithm based on network analysis and big data. International Journal of Civil Engineering and Technology, vol. 10, no. 2, pp. 291-300, Article Id: IJCIET_10_02_032.
- 30. Pyrke, S. (2012). Social network analysis in construction. John Wiley & Sons.
- 31. Scott, J. (2000). Social Network Analysis: A Handbook, 2nd edition. London-Thousands Oaks, California: SAGE Publications Ltd.
- 32. Shum, S.B., Cannavacciuolo, L., De Liddo, A., Iandoli, L., Quinto, I. (2011). Using social network analysis to support collective decision-making process. International Journal of Decision Support System Technology (IJDSST), vol. 3, no. 2, pp. 15-31, 10.4018/jdsst.2011040102.
- 33. Sparrowe, R.T., Liden, R.C., Wayne, S.J., Kraimer, M.L. (2001). Social networks and the performance of individuals and groups. Academy Of Management Journal, vol. 44, no. 2, pp. 316-325, https://doi.org/10.2307/3069458.
- 34. Sunstein, C.R., Hastie, R. (2014). Making dumb groups smarter. Harvard Business Review, vol. 92, no. 12, pp. 90-98, https://hbr.org/2014/12/making-dumb-groups-smarter, 21.03.2022.
- 35. Visier, The Age of People Analytics Research Report. https://hello.visier.com/age-of- people-analytics-research-report/, 19.02.2020.
- 36. Wasserman, S., Faust, K. (1994). Social Network Analysis: Methods and Applications (Vol. 8). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511815478.
- 37. Wawrzynek, Ł. (2015). Sieciowe uwarunkowania rozwijania potencjału innowacyjnego systemu zarządzania. Management Forum, vol. 3, no. 4, pp. 18-26, doi:10.15611/ mf.2015.4.03.
- 38. Welles, B.F., Xu, W. (2018). Network visualization and problem-solving support: A cognitive fit study. Social Networks, vol. 54, pp. 162-167, https://doi.org/10.1016/ j.socnet.2018.01.005.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-00471c57-825c-427b-8e34-690cd5713997